dill package documentation¶
dill: serialize all of python¶
About Dill¶
dill
extends python’s pickle
module for serializing and de-serializing
python objects to the majority of the built-in python types. Serialization
is the process of converting an object to a byte stream, and the inverse
of which is converting a byte stream back to a python object hierarchy.
dill
provides the user the same interface as the pickle
module, and
also includes some additional features. In addition to pickling python
objects, dill
provides the ability to save the state of an interpreter
session in a single command. Hence, it would be feasable to save a
interpreter session, close the interpreter, ship the pickled file to
another computer, open a new interpreter, unpickle the session and
thus continue from the ‘saved’ state of the original interpreter
session.
dill
can be used to store python objects to a file, but the primary
usage is to send python objects across the network as a byte stream.
dill
is quite flexible, and allows arbitrary user defined classes
and functions to be serialized. Thus dill
is not intended to be
secure against erroneously or maliciously constructed data. It is
left to the user to decide whether the data they unpickle is from
a trustworthy source.
dill
is part of pathos
, a python framework for heterogeneous computing.
dill
is in active development, so any user feedback, bug reports, comments,
or suggestions are highly appreciated. A list of issues is located at https://github.com/uqfoundation/dill/issues, with a legacy list maintained at https://uqfoundation.github.io/pathos-issues.html.
Major Features¶
dill
can pickle the following standard types:
- none, type, bool, int, long, float, complex, str, unicode,
- tuple, list, dict, file, buffer, builtin,
- both old and new style classes,
- instances of old and new style classes,
- set, frozenset, array, functions, exceptions
dill
can also pickle more ‘exotic’ standard types:
- functions with yields, nested functions, lambdas,
- cell, method, unboundmethod, module, code, methodwrapper,
- dictproxy, methoddescriptor, getsetdescriptor, memberdescriptor,
- wrapperdescriptor, xrange, slice,
- notimplemented, ellipsis, quit
dill
cannot yet pickle these standard types:
- frame, generator, traceback
dill
also provides the capability to:
- save and load python interpreter sessions
- save and extract the source code from functions and classes
- interactively diagnose pickling errors
Current Release¶
This documentation is for version dill-0.3.4.dev0
.
The latest released version of dill
is available from:
dill
is distributed under a 3-clause BSD license.
>>> import dill
>>> dill.license()
Development Version¶
You can get the latest development version with all the shiny new features at:
If you have a new contribution, please submit a pull request.
Installation¶
dill
is packaged to install from source, so you must
download the tarball, unzip, and run the installer:
[download]
$ tar -xvzf dill-0.3.3.tar.gz
$ cd dill-0.3.3
$ python setup py build
$ python setup py install
You will be warned of any missing dependencies and/or settings after you run the “build” step above.
Alternately, dill
can be installed with pip
or easy_install
:
$ pip install dill
Requirements¶
dill
requires:
python
, version == 2.7 or version >= 3.6, orpypy
Optional requirements:
setuptools
, version >= 0.6pyreadline
, version >= 1.7.1 (on windows)objgraph
, version >= 1.7.2
More Information¶
Probably the best way to get started is to look at the documentation at
http://dill.rtfd.io. Also see dill.tests
for a set of scripts that
demonstrate how dill
can serialize different python objects. You can
run the test suite with python -m dill.tests
. The contents of any
pickle file can be examined with undill
. As dill
conforms to
the pickle
interface, the examples and documentation found at
http://docs.python.org/library/pickle.html also apply to dill
if one will import dill as pickle
. The source code is also generally
well documented, so further questions may be resolved by inspecting the
code itself. Please feel free to submit a ticket on github, or ask a
question on stackoverflow (@Mike McKerns).
If you would like to share how you use dill
in your work, please send
an email (to mmckerns at uqfoundation dot org).
Citation¶
If you use dill
to do research that leads to publication, we ask that you
acknowledge use of dill
by citing the following in your publication:
M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
"Building a framework for predictive science", Proceedings of
the 10th Python in Science Conference, 2011;
http://arxiv.org/pdf/1202.1056
Michael McKerns and Michael Aivazis,
"pathos: a framework for heterogeneous computing", 2010- ;
https://uqfoundation.github.io/pathos.html
Please see https://uqfoundation.github.io/pathos.html or http://arxiv.org/pdf/1202.1056 for further information.
-
citation
()¶ print citation
-
extend
(use_dill=True)¶ add (or remove) dill types to/from the pickle registry
by default,
dill
populates its types topickle.Pickler.dispatch
. Thus, alldill
types are available upon calling'import pickle'
. To drop alldill
types from thepickle
dispatch, use_dill=False.Parameters: use_dill (bool, default=True) – if True, extend the dispatch table. Returns: None
-
license
()¶ print license
-
load_types
(pickleable=True, unpickleable=True)¶ load pickleable and/or unpickleable types to
dill.types
dill.types
is meant to mimic thetypes
module, providing a registry of object types. By default, the module is empty (for import speed purposes). Use theload_types
function to load selected object types to thedill.types
module.Parameters: - pickleable (bool, default=True) – if True, load pickleable types.
- unpickleable (bool, default=True) – if True, load unpickleable types.
Returns: None